Update app.py

app.py

@@ -7,239 +7,6 @@ from google.genai import types
 from mcp import ClientSession, StdioServerParameters
 from mcp.client.stdio import stdio_client
 
-# MCP-Server Konfiguration
-server_params = StdioServerParameters(
-    command="npx",
-    args=[
-        "mcp-remote",
-        "https://mgokg-db-timetable-api.hf.space/gradio_api/mcp/"
-    ]
-)
-
-async def generate1(input_text):
-    try:
-        client = genai.Client(api_key=os.environ.get("GEMINI_API_KEY"))
-    except Exception as e:
-        return f"Fehler bei der Initialisierung: {e}", ""
-    
-    model = "gemini-2.5-flash"
-    
-    try:
-        # MCP-Session aufbauen
-        async with stdio_client(server_params) as (read, write):
-            async with ClientSession(read, write) as session:
-                await session.initialize()
-                
-                # MCP-Tools abrufen
-                mcp_tools_data = await session.list_tools()
-                
-                # Tools in Gemini-kompatibles Format konvertieren
-                function_declarations = []
-                
-                # 1. MCP Tools hinzufügen
-                for tool in mcp_tools_data.tools:
-                    schema = tool.inputSchema if tool.inputSchema else {
-                        "type": "object",
-                        "properties": {},
-                        "required": []
-                    }
-                    
-                    function_declarations.append(
-                        types.FunctionDeclaration(
-                            name=tool.name,
-                            description=tool.description or "MCP Tool",
-                            parameters=schema
-                        )
-                    )
-                
-                # 2. Google Search Tool hinzufügen (als Function Declaration)
-                # Die Gemini API erwartet Google Search als spezielles Tool
-                google_search_declaration = types.FunctionDeclaration(
-                    name="google_search",
-                    description="Search the internet for current information, news, facts, and general knowledge. Use this for questions about current events, weather, general knowledge, or when you need up-to-date information from the web.",
-                    parameters={
-                        "type": "object",
-                        "properties": {
-                            "query": {
-                                "type": "string",
-                                "description": "The search query to look up on Google"
-                            }
-                        },
-                        "required": ["query"]
-                    }
-                )
-                function_declarations.append(google_search_declaration)
-                
-                # Alle Tools kombinieren
-                tools = [types.Tool(function_declarations=function_declarations)]
-                
-                # System Prompt zur Tool-Auswahl
-                system_instruction = """You are a helpful assistant with access to two types of tools:
-
-1. TRAIN CONNECTION TOOLS (MCP): Use these ONLY when the user asks about train connections, schedules, routes, or German railway (DB) information. Available tools: """ + ", ".join([t.name for t in mcp_tools_data.tools]) + """
-
-2. GOOGLE SEARCH: Use this for ALL other queries - general knowledge, current events, weather, news, calculations, or any topic not related to train connections.
-
-Choose the appropriate tool based on the user's intent. For train connections, use the MCP tools. For everything else, use Google Search."""
-
-                contents = [types.Content(
-                    role="user", 
-                    parts=[types.Part.from_text(text=input_text)]
-                )]
-                
-                # Erster API-Aufruf
-                response = await client.aio.models.generate_content(
-                    model=model,
-                    contents=contents,
-                    config=types.GenerateContentConfig(
-                        tools=tools,
-                        temperature=0.4,
-                        system_instruction=system_instruction
-                    )
-                )
-                
-                # Agentic Loop für Tool-Calls
-                turn_count = 0
-                max_turns = 5
-                
-                while response.candidates and turn_count < max_turns:
-                    candidate = response.candidates[0]
-                    
-                    if not hasattr(candidate, 'content') or not candidate.content:
-                        break
-                        
-                    function_calls = [
-                        part for part in candidate.content.parts 
-                        if hasattr(part, 'function_call') and part.function_call
-                    ]
-                    
-                    if not function_calls:
-                        break
-                    
-                    turn_count += 1
-                    contents.append(candidate.content)
-                    tool_responses = []
-                    
-                    for part in function_calls:
-                        fc = part.function_call
-                        tool_name = fc.name
-                        tool_args = dict(fc.args) if fc.args else {}
-                        
-                        try:
-                            # Unterscheide zwischen MCP-Tools und Google Search
-                            if tool_name == "google_search":
-                                # Google Search über Gemini's eingebautes Tool
-                                # Wir simulieren hier den Aufruf durch einen neuen Request mit google_search Tool
-                                search_response = await client.aio.models.generate_content(
-                                    model=model,
-                                    contents=[types.Content(
-                                        role="user",
-                                        parts=[types.Part.from_text(text=f"Search Google for: {tool_args.get('query', '')}")]
-                                    )],
-                                    config=types.GenerateContentConfig(
-                                        tools=[types.Tool(google_search=types.GoogleSearch())],
-                                        temperature=0.4
-                                    )
-                                )
-                                result_text = search_response.text
-                                
-                            else:
-                                # MCP-Tool ausführen
-                                tool_result = await session.call_tool(tool_name, tool_args)
-                                
-                                if tool_result.isError:
-                                    result_text = f"Error: {tool_result.content[0].text if tool_result.content else 'Unknown error'}"
-                                else:
-                                    result_text = tool_result.content[0].text if tool_result.content else "No result"
-                            
-                            tool_responses.append(
-                                types.FunctionResponse(
-                                    name=tool_name,
-                                    response={"result": result_text}
-                                )
-                            )
-                            
-                        except Exception as e:
-                            tool_responses.append(
-                                types.FunctionResponse(
-                                    name=tool_name,
-                                    response={"error": str(e)}
-                                )
-                            )
-                    
-                    contents.append(types.Content(role="user", parts=[
-                        types.Part.from_function_response(
-                            name=tr.name,
-                            response=tr.response
-                        ) for tr in tool_responses
-                    ]))
-                    
-                    # Nächster API-Aufruf
-                    response = await client.aio.models.generate_content(
-                        model=model,
-                        contents=contents,
-                        config=types.GenerateContentConfig(
-                            tools=tools, 
-                            temperature=0.4,
-                            system_instruction=system_instruction
-                        )
-                    )
-                
-                return response.text, ""
-    
-    except Exception as e:
-        import traceback
-        return f"Fehler während der Verarbeitung: {str(e)}\n\n{traceback.format_exc()}", ""
-
-# Gradio UI Wrapper
-def generate(input_text):
-    try:
-        return asyncio.run(generate1(input_text))
-    except Exception as e:
-        import traceback
-        return f"UI Fehler: {str(e)}\n\n{traceback.format_exc()}", ""
-
-if __name__ == '__main__':
-    with gr.Blocks() as demo:
-        gr.Markdown("# Gemini 2.5 Flash + Google Search + DB Timetable (MCP)")
-        
-        with gr.Row():
-            with gr.Column():
-                input_textbox = gr.Textbox(
-                    lines=3, 
-                    label="Anfrage", 
-                    placeholder="z.B. Wie komme ich von Berlin nach Hamburg? oder Was ist die Hauptstadt von Frankreich?"
-                )
-                submit_button = gr.Button("Senden", variant="primary")
-            
-            with gr.Column():
-                output_textbox = gr.Markdown(label="Antwort")
-                status_textbox = gr.Textbox(label="Status", interactive=False)
-        
-        submit_button.click(
-            fn=generate,
-            inputs=input_textbox,
-            outputs=[output_textbox, status_textbox]
-        )
-        
-        # Enter-Taste unterstützung
-        input_textbox.submit(
-            fn=generate,
-            inputs=input_textbox,
-            outputs=[output_textbox, status_textbox]
-        )
-    
-    demo.launch(show_error=True, share=False)
-"""
-import gradio as gr
-import os
-import asyncio
-from typing import List
-from google import genai
-from google.genai import types
-from mcp import ClientSession, StdioServerParameters
-from mcp.client.stdio import stdio_client
-
 # MCP-Server Konfiguration (ohne ungültigen Transport-Parameter)
 server_params = StdioServerParameters(
     command="npx",
@@ -255,7 +22,7 @@ async def generate(input_text):
     except Exception as e:
         return f"Fehler bei der Initialisierung: {e}", ""
 
-    model = "gemini-2.5-flash"
+    model = "gemini-flash-latest"
 
     try:
         # MCP-Session aufbauen
@@ -450,5 +217,4 @@ if __name__ == '__main__':
         input_textbox = gr.Textbox(lines=3, label="", placeholder="Enter message here...")
         submit_button = gr.Button("send")
         submit_button.click(fn=generate,inputs=input_textbox,outputs=[output_textbox, input_textbox])
-    demo.launch(show_error=True)
-"""
+    demo.launch(show_error=True)